Biofouling is a long-standing problem in many scientific and technological applications, thus development and understanding of highly bioinert and biocompatible antifouling materials are crucial for many fundamental and practical applications. The current materials design strategy often encounters the difficulties of inconsistent datasets and heuristically cost- and time-extensive optimization procedures. This work aims to propose a potential transforming strategy, combining mathematical modeling, molecular simulations, and experiments, to setup a simple yet robust polymer and coating system to collect a reliable benchmarking dataset for better assessing the component-structure-property-performance relationship of antifouling polymer coatings, and then to use this reliable source to develop a computational predictive model for the structural-based design of next-generation antifouling materials. This proposed research will contribute new knowledge related to new antifouling design and manufacture, promoting both the progress of science and advancing national prosperity. Educational and outreach activities will focus on strategies to enhance recruitment and retention of all-level students particularly from underrepresented groups and to help them to learn interdisciplinary knowledge and skills from polymer physics/chemistry, lab-on-chip design, and ergonomic engineering, thus promoting the next-generation of STEM education.
The main objective of this proposal is to develop a novel, cheminformatics-based strategy combining computational and experimental techniques to design new distinctive antifouling polymers by understanding and engineering the interfacial interactions between antifouling polymers and fouling species at different spatial and time scales. A synergistic large-data-driven computational approach will be developed to study interfacial interactions between proteins and polymer brushes at atomic level, and then to correlate interfacial interactions with their structure-property relationships and antifouling potentials. Then, a series of polymer brushes, as selected by computational design, with well-controlled surface properties, will be synthesized and tested for their combinatory effects of polymer chemistries and brush topological parameters on their antifouling performance. Finally, a QSAR model will be developed to better reconcile all quantitative computational and experimental data from the benchmarking dataset to describe a relationship among monomer structures, polymer architectures, structural-dependent physical/chemical/biological properties, and antifouling performance. The obtained antifouling materials can also serve as a basis for exploration of other bioactive properties for controlled nanoparticle synthesis, tissue engineering, and biocompatible surface modification. The design strategies will have potential to be applied to the development of other polymer materials, such as antibacterial materials, self-assembling materials, and hydrogel materials.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
